Multi-channel (e.g. three color band, luminance band) imagery sensing devices, such as a digital RGB video camera, typically produce output signals whose sampling frequencies differ, with one channel (usually one of the green or the luminance channel) being fully sampled, while the other channels (the red and blue channels) carry lower resolution data. For example, in a miniaturized charge-coupled device camera, the amount of green information may be two or three times that of the red or blue channels. Moreover, in color image compression telecommunication systems, it is common practice to subsample the chrominance channels prior to applying the data to a compression mechanism, for the purpose of further reducing the amount of data to be transmitted.
Because of this reduction in the amount of information through which the original image has been defined, upon reconstruction, it is necessary to fill in or interpolate values for non-sampled image locations of the lower resolution channel. A widespread technique for carrying out the interpolation process is to conduct a one or two-dimensional linear interpolation for computing values of image locations, where there is no chrominance information, from adjacent pixels where chrominance values are available. Typically, the interpolated value is a color difference signal, such as an I, Q, R-G, or B-G signal. Unfortunately, such linear interpolation process yields color artifacts (a blurring or smearing of the image) at edges between regions of different color, so that the colored component of the edge is not as sharp as the luminance component, thereby reducing the quality of both photographic images and video images of real scenes.